The dataset contains 4,337 recorded incidents, each representing a confirmed attack against humanitarian operations between 1997 and 2025. Structured at the event level, these records document operational disruptions — not individuals or fixed locations. As such, the data is best understood as a chronicle of threat encounters, not a risk likelihood model.
Certain fields — such as victim counts and agency involvement — offer strong fidelity, thanks to uniforms and ICRC - compliant markings. These details enable reliable quantification of affected nationals vs. internationals and targeted organizations such as the UN, INGOs, and Red Cross affiliates.
However, critical intelligence gaps persist. Variables like actor name, motive, and means of attack are frequently marked as “Unknown.” This reflects a practical reality: in high - risk environments, immediate triage and rescue take precedence over detailed record-keeping, often resulting in delayed or degraded data collection.
From an analytical standpoint, these incidents should ideally be contextualized against baseline rates — such as the number of deployed personnel, mission types, or vehicle movements in each region. While unavailable in this dataset, such baseline indicators remain a critical frontier for future humanitarian intelligence systems.